Image denoising for laser ultrasonic inspection of wire arc additive-manufactured components with a rough surface

Abstract

ABSTRACT Laser ultrasonic testing (LUT) is a non-contact and non-destructive testing (NDT) technique which can detect the wire arc additive manufacturing (WAAM) component defect in hot state. However, the complex surface topography of the WAAM component induces a low signal to noise ratio (SNR) and a poor detection sensitivity. In this paper, a denoising method based on improved empirical mode decomposition with adaptive noise (ICEEMDAN) and Wavelet Packet Transform (WPT) was applied in the LUT of the WAAM component. All the signals in the LUT scan maps with low SNR were decomposed into a series of intrinsic mode functions (IMFs) using ICEEMDAN. The Pearson correlation coefficient of the original signal and the IMFs were calculated. The high frequency (HF) and low frequency (LF) IMFs with correlation coefficients under the threshold were denoised using WPT and deleted, respectively. The denoised IMFs and the IMFs without processing were stacked up to compose the denoised signal and plot the denoised scan maps. The denoising results show that the proposed method improved the LUT efficiency and sensitivity. Finally, the denoising method was applied and verified in the LUT of the WAAM nuclear power pipeline nozzle.